Nanofluid PCMs for thermal energy storage: Latent heat reduction mechanisms and a numerical study of effective thermal storage performance

Abstract

Abstract The latent heat of fusion of paraffin-based nanofluids has been examined to investigate the use of enhanced phase change materials (PCMs) for thermal energy storage (TES) applications. The nanofluid approach has often been exploited to enhance thermal conductivity of PCMs, but the effects of particle addition on other thermal properties affecting TES are relatively ignored. An experimental study of paraffin-based nanofluids containing various particle sizes of multi-walled carbon nanotubes has been conducted to investigate the effect of nanoparticles on latent heat of fusion. Results demonstrated that the magnitude of nanofluid latent heat reduction increases for smaller diameter particles in suspension. Three possible mechanisms – interfacial liquid layering, Brownian motion, and particle clustering – were examined to explain further reduction in latent heat, through the weakening of molecular bond structures. Although additional research is required to explore detailed mechanisms, experimental evidence suggests that interfacial liquid layering and Brownian motion cannot explain the degree of latent heat reduction observed. A finite element model is also presented as a method of quantifying nanofluid PCM energy storage performance. Thermal properties based on modified effective medium theory and an empirical relation for latent heat of fusion were applied as model parameters to determine energy stored and extracted over a given period of time. The model results show that while micro-scale particle inclusions exhibit some performance enhancement, nanoparticles in PCMs provide no significant improvement in TES performance. With smaller particles, the enhancement in thermal conductivity is not significant enough to overcome the reduction in latent heat of fusion, and less energy is stored over the PCM charge period. Therefore, the nanofluid approach may not be justifiable for energy storage applications. However, since the model parameters are dependent on the material properties of the system observed, storage performance may vary for differing nanofluid materials.